Untitled Quiz

Concepts

• A concept is a general idea used to summarize a specific phenomenon
• Concepts can be concrete, abstract, tangible, or intangible
• Examples of concepts include "height" and "love"

Transferring Concepts into Measurable Variables

• A variable represents a concept in its variation of degree, varieties, or occurrence
• A variable is a characteristic of a thing that can assume varying degrees or values
• Most variables are truly variable, meaning they have multiple categories or variations

Example: Concept and Variable

• Political participation is a concept
• Variables related to political participation include:
  • Voted or not
  • How many times a person has voted
  • What party a person votes for

Conceptualization

• The process of conceptualization involves defining the meaning of a concept
• Conceptualization involves moving between loose ideas and finding a word that best describes them
• Sometimes, new terms need to be created to encompass a concept
• Dimensions represent subgroups of a concept

Operationalizing Choices

• Operationalization is the process of converting concepts into measurable terms
• It involves developing research procedures that result in empirical observations
• For example, socioeconomic status (SES) can be operationalized by combining income and education levels

Variable Attribute Choices

• Variable attributes must be exhaustive and exclusive
• They represent the full range of possible variations

Degree of Precision

• The level of precision in variable attributes depends on the research interest
• Consider whether it is better to include too much or too little information in a variable

Variables

• The dependent variable is the variable that is measured by the researcher
• The independent variable is the one that the researcher manipulates
• For example, in a study about the effects of a new educational program, the program is the independent variable and student achievement is the dependent variable

Qualitative and Quantitative Variables

• Qualitative variables are composed of categories that cannot be compared in terms of magnitude
• Quantitative variables can be ordered with respect to magnitude on some dimension
• Continuous variables are quantitative variables that can be measured with an arbitrary degree of precision
• Discrete variables are quantitative variables where values can differ only by well-defined increments

Levels of Measurement

• Nominal
• Ordinal
• Interval
• Ratio

Nominal Measures

• Offer only a name or label for a variable
• There is no ranking involved
• They are not numerically related
• Examples include gender and race

Ordinal Measures

• Variables with attributes that can be rank-ordered
• One response can be considered more or less than another
• The distance between attributes lacks meaning
• An example is socioeconomic class (lower, middle, upper)

Interval Measures

• The distance separating attributes has meaning and is standardized
• A "0" value does not mean the variable is not present
• An example is a score on an ACT test

Ratio Measures

• Attributes have a "true zero point" which has meaning
• Examples include waist and biceps measurements
• Allows for the creation of ratios

Hypotheses

• Hypotheses are untested statements that specify a relationship between two or more variables
• An example is "Milk drinkers make better lovers"

Characteristics of a Hypothesis

• States a relationship between two or more variables
• Is stated affirmatively
• Can be tested with empirical evidence
• Most useful when it makes a comparison
• States how multiple variables are related
• Has a logical explanation for the relationship

Positive and Negative (Inverse) Relationships

• Positive: as values of independent variable increase, the values of the dependent variable increase
• Negative: as values of independent variable increase, the values of the dependent variable decrease (or vice versa)

Two-Directional Hypotheses

• General expression of a hypothesis
• Suggests that groups are different or concepts are related, but without specifying the direction of the difference
• An example is "Men and women trust UK security differently"

One-Directional Hypotheses

• Specific expression of a hypothesis
• Specifies the precise direction of the relationship between the dependent and independent variables
• An example is "Women have greater trust in UK security compared to men"

Determining Quality of Measurement

• Accuracy and consistency in measurement are essential
• Validity refers to accuracy
• Reliability refers to consistency

Reliability

• The extent to which the same research technique applied to the same object will give the same results
• Reliability does not ensure accuracy, as a measure can be reliable but inaccurate due to bias in the measure or data collection

Validity

• The extent to which a measure reflects what we think or want it to be measuring

Face Validity

• The measure seems to be related to what we are interested in finding out, even if it doesn't fully encompass the concept
• Example: Using grades to measure intellectual capacity has high face validity, while using number of close friends has low face validity

Criterion Validity

• The measure is predictive of some external criterion
• Example: ACT scores have high criterion validity as they potentially predict success in college

Construct Validity

• The measure is logically related to another variable as conceptualized
• Example: Financial stability might not be strongly related to happiness, resulting in low construct validity when used to measure happiness

Content Validity

• How much a measure covers a range of meanings, and whether it covers all relevant dimensions
• Example: A measure of prejudice that only asks questions about race might lack content validity, as it doesn't address other forms of prejudice

Methodological Approaches, Reliability, and Validity

• Qualitative research methods tend to have high validity and lower reliability
• Quantitative research methods tend to have lower validity and higher reliability